Managing virtual machines according to network bandwidth

ABSTRACT

A processor-implemented method manages virtual machines that execute on physical servers in a server cloud. One or more processors establish a maximum network bandwidth percentage for a physical server in the server cloud. The maximum network bandwidth percentage is a percentage of a total network bandwidth capability designed for the first physical server. Response time for operational requests to one or more virtual machines on the first physical server changes beyond a predefined differential in response to the maximum network bandwidth percentage being reached. In response to the NIC controller device on the first physical server determining that the maximum network bandwidth percentage for the first physical server is exceeded, a cloud service hypervisor device moves one or more virtual machines on the first physical server to a second physical server in the server cloud.

BACKGROUND

The present disclosure relates to the field of virtual machines, andspecifically to the field of virtual machines running on physicalcomputers in a server cloud. Still more specifically, the presentdisclosure relates to configuring and deploying virtual machines onphysical computers in a server cloud.

SUMMARY

In an embodiment of the present invention, a processor-implementedmethod manages virtual machines that execute on physical servers in aserver cloud. One or more processors establish a maximum networkbandwidth percentage for a physical server in the server cloud. Themaximum network bandwidth percentage is a percentage of a total networkbandwidth capability designed for the first physical server. Responsetime for operational requests to one or more virtual machines on thefirst physical server changes beyond a predefined differential inresponse to the maximum network bandwidth percentage being reached. Anetwork interface card (NIC) controller device on the first physicalserver determines that the maximum network bandwidth percentage for thefirst physical server is exceeded. In response to the NIC controllerdevice on the first physical server determining that the maximum networkbandwidth percentage for the first physical server is exceeded, a cloudservice hypervisor device moves one or more virtual machines on thefirst physical server to a second physical server in the server cloud.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a cloud computing node according to an embodiment of thepresent invention;

FIG. 2 illustrates a cloud computing environment according to anembodiment of the present invention;

FIG. 3 depicts abstraction model layers according to an embodiment ofthe present invention;

FIG. 4 illustrates an exemplary server cloud in which one or moreembodiments of the present invention may be incorporated;

FIGS. 5A-5B depicts network bandwidth utilization percentages of twoservers depicted in FIG. 4;

FIG. 6 illustrates response delays in a physical server according to apercentage of network bandwidth being utilized;

FIG. 7 depicts tables showing a movement of various virtual machinesfrom a first physical server to a second physical server within a servercloud, based on network bandwidth percentage utilization by the firstphysical server; and

FIG. 8 is a high-level flowchart of one or more steps performed by oneor more processors and/or other hardware devices to manage virtualmachine deployment to physical servers in a server cloud.

DETAILED DESCRIPTION

The present invention may be a system, a method, and/or a computerprogram product. The computer program product may include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

It is to be understood that in one or more embodiments, the presentinvention is capable of being implemented in a cloud computingenvironment.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g. networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, network bandwidth, and active user accounts). Resource usagecan be monitored, controlled, and reported providing transparency forboth the provider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based e-mail).The consumer does not manage or control the underlying cloudinfrastructure including network, servers, operating systems, storage,or even individual application capabilities, with the possible exceptionof limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring now to FIG. 1, a schematic of an example of a cloud computingnode is shown. Cloud computing node 10 is only one example of a suitablecloud computing node and is not intended to suggest any limitation as tothe scope of use or functionality of embodiments of the inventiondescribed herein. Regardless, cloud computing node 10 is capable ofbeing implemented and/or performing any of the functionality set forthhereinabove.

In cloud computing node 10 there is a computer system/server 12, whichis operational with numerous other general purpose or special purposecomputing system environments or configurations. Examples of well-knowncomputing systems, environments, and/or configurations that may besuitable for use with computer system/server 12 include, but are notlimited to, personal computer systems, server computer systems, thinclients, thick clients, hand-held or laptop devices, multiprocessorsystems, microprocessor-based systems, set top boxes, programmableconsumer electronics, network PCs, minicomputer systems, mainframecomputer systems, and distributed cloud computing environments thatinclude any of the above systems or devices, and the like.

Computer system/server 12 may be described in the general context ofcomputer system-executable instructions, such as program modules, beingexecuted by a computer system. Generally, program modules may includeroutines, programs, objects, components, logic, data structures, and soon that perform particular tasks or implement particular abstract datatypes. Computer system/server 12 may be practiced in distributed cloudcomputing environments where tasks are performed by remote processingdevices that are linked through a communications network. In adistributed cloud computing environment, program modules may be locatedin both local and remote computer system storage media including memorystorage devices.

As shown in FIG. 1, computer system/server 12 in cloud computing node 10is shown in the form of a general-purpose computing device. Thecomponents of computer system/server 12 may include, but are not limitedto, one or more processors or processing units 16, a system memory 28,and a bus 18 that couples various system components including systemmemory 28 to processor 16.

Bus 18 represents one or more of any of several types of bus structures,including a memory bus or memory controller, a peripheral bus, anaccelerated graphics port, and a processor or local bus using any of avariety of bus architectures. By way of example, and not limitation,such architectures include Industry Standard Architecture (ISA) bus,Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, VideoElectronics Standards Association (VESA) local bus, and PeripheralComponent Interconnects (PCI) bus.

Computer system/server 12 typically includes a variety of computersystem readable media. Such media may be any available media that isaccessible by computer system/server 12, and it includes both volatileand non-volatile media, removable and non-removable media.

System memory 28 can include computer system readable media in the formof volatile memory, such as random access memory (RAM) 30 and/or cachememory 32. Computer system/server 12 may further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, storage system 34 can be provided forreading from and writing to a non-removable, non-volatile magnetic media(not shown and typically called a “hard drive”). Although not shown, amagnetic disk drive for reading from and writing to a removable,non-volatile magnetic disk (e.g., a “floppy disk”), and an optical diskdrive for reading from or writing to a removable, non-volatile opticaldisk such as a CD-ROM, DVD-ROM or other optical media can be provided.In such instances, each can be connected to bus 18 by one or more datamedia interfaces. As will be further depicted and described below,memory 28 may include at least one program product having a set (e.g.,at least one) of program modules that are configured to carry out thefunctions of embodiments of the invention.

Program/utility 40, having a set (at least one) of program modules 42,may be stored in memory 28 by way of example, and not limitation, aswell as an operating system, one or more application programs, otherprogram modules, and program data. Each of the operating system, one ormore application programs, other program modules, and program data orsome combination thereof, may include an implementation of a networkingenvironment. Program modules 42 generally carry out the functions and/ormethodologies of embodiments of the invention as described herein.

Computer system/server 12 may also communicate with one or more externaldevices 14 such as a keyboard, a pointing device, a display 24, etc.;one or more devices that enable a user to interact with computersystem/server 12; and/or any devices (e.g., network card, modem, etc.)that enable computer system/server 12 to communicate with one or moreother computing devices. Such communication can occur via I/O interfaces22. Still yet, computer system/server 12 can communicate with one ormore networks such as a local area network (LAN), a general wide areanetwork (WAN), and/or a public network (e.g., the Internet) via networkadapter 20. As depicted, network adapter 20 communicates with the othercomponents of computer system/server 12 via bus 18. It should beunderstood that although not shown, other hardware and/or softwarecomponents could be used in conjunction with computer system/server 12.Examples, include, but are not limited to: microcode, device drivers,redundant processing units, external disk drive arrays, RAID systems,tape drives, and data archival storage systems, etc.

In one or more embodiments of the present invention, external devices 14utilize the architecture of the computer system/server 12 shown inFIG. 1. Similarly, some or all of the architecture of computersystem/server 10 can be implemented in the physical servers 402 a-402 band/or the client computer 404 shown in FIG. 4.

Referring now to FIG. 2, illustrative cloud computing environment 50 isdepicted. As shown, cloud computing environment 50 comprises one or morecloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Nodes 10 maycommunicate with one another. They may be grouped (not shown) physicallyor virtually, in one or more networks, such as Private, Community,Public, or Hybrid clouds as described hereinabove, or a combinationthereof. This allows cloud computing environment 50 to offerinfrastructure, platforms and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 2 are intended to be illustrative only and that computing nodes10 and cloud computing environment 50 can communicate with any type ofcomputerized device over any type of network and/or network addressableconnection (e.g., using a web browser).

Referring now to FIG. 3, a set of functional abstraction layers providedby cloud computing environment 50 (FIG. 2) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 3 are intended to be illustrative only and embodiments of theinvention are not limited thereto. As depicted, the following layers andcorresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include mainframes, in oneexample IBM® zSeries® systems; RISC (Reduced Instruction Set Computer)architecture based servers, in one example IBM pSeries® systems; IBMxSeries® systems; IBM BladeCenter® systems; NeXtScale; storage devices;networks and networking components. Examples of software componentsinclude network application server software, in one example IBM WebSphere® application server software; and database software, in oneexample IBM DB2® database software. (IBM, zSeries, pSeries, xSeries,BladeCenter, NeXtScale, Web Sphere, and DB2 are trademarks ofInternational Business Machines Corporation registered in manyjurisdictions worldwide)

Virtualization layer 62 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers;virtual storage; virtual networks, including virtual private networks;virtual applications and operating systems; and virtual clients.

In one example, management layer 64 may provide the functions describedbelow. Resource provisioning provides dynamic procurement of computingresources and other resources that are utilized to perform tasks withinthe cloud computing environment. Metering and Pricing provide costtracking as resources are utilized within the cloud computingenvironment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal provides access to the cloud computing environment forconsumers and system administrators. Service level management providescloud computing resource allocation and management such that requiredservice levels are met. Service Level Agreement (SLA) planning andfulfillment provide pre-arrangement for, and procurement of, cloudcomputing resources for which a future requirement is anticipated inaccordance with an SLA.

Workloads layer 66 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation; software development and lifecycle management; virtualclassroom education delivery; data analytics processing; transactionprocessing; and managing virtual machines, as described herein, and asrepresented by the “Virtual Machine Deployment Processing” found inworkloads layer 66.

With reference now to FIG. 4, an exemplary server cloud 400 in which oneor more embodiments of the present invention may be incorporated ispresented. As shown, server cloud 400 is made up of multiple physicalservers 402 a-402 b (where “b” is an integer). Depicted are two of thephysical servers 402 a-402 b, which are referred to herein as server #1and server #2. In one or more embodiments of the present invention, oneor more of the physical servers 402 a-402 b are communicably connected(i.e., are able to exchange messages, instructions, data, virtualmachines, etc.).

A client computer 404 is able to utilize the resources within the servercloud 400. In one or more embodiments of the present invention, theresources used by the client computer 404 are virtual machines. Avirtual machine is an emulation of a real computer. That is, a virtualmachine responds to inputs, instructions, signals, etc. just like a realcomputer would, but such inputs, instructions, signals, etc. aremanipulated by software within a physical computer that may or may notbe the same type of computer being emulated. The physical computer(often a server) is able to emulate multiple computers (known as virtualmachines, or “VMs”).

Thus, the physical computers (e.g., server #1 (402 a) and server #2 (402b)) within the server cloud 400 are able to emulate multiple computers,shown as virtual machines 406 a-406 n (where “n” is an integer) inserver #1, and as virtual machines 408 a-408 n (where “n” is an integer)in server #2.

Traffic to and from the virtual machines are via a network interfacecard (NIC) hardware device. A network interface card, also known as anetwork interface controller, network adapter, local area network (LAN)adapter, etc., is a computer hardware device the connects a computer toa computer network. As depicted in FIG. 4, server #1 uses NIC 410 a,while server #2 uses NIC 410 b to connect to other servers within theserver cloud 400 and to devices outside of the server cloud 400, such asclient computer 404.

Each NIC utilizes a management information base (MIB). An MIB is adatabase used to manage resources in a cloud or other network ofresources. Information in the MIB is specific for managed resources inthe cloud. The MIB contains object instances, which are identified byobject identifiers (OIDs), which describe characteristics of the managedresources, such as their identity, their type (e.g., a server, a storagedevice, an application, etc.), etc., as well as current states (e.g.,turned on or off, register values within the resource, workload queuelevels, etc.). Thus, NIC 402 a in server #1 uses MIB 412 a, while NIC402 b in server #2 uses MIB 412 b.

The MIBs (e.g., MIB 412 a and MIB 412 b) are used by a cloud servicehypervisor device 414 to manage resources in the server cloud 400, bothby receiving information from the resources in the form of SNMP traps(which are received by a trap receiver within the cloud servicehypervisor device 414), and by transmitting instructions from the cloudservice hypervisor device 414 to the physical servers 402 a-402 b withinthe server cloud 400 (in the form of a GET/SET request). In one or moreembodiments, the cloud service hypervisor device 414 is a hardwaredevice that is constructed to solely perform the function of directingmessages to the servers 402 a-402 b (e.g., as a router).

The NICs 410 a-410 b and/or the cloud service hypervisor device 414 arethus able to monitor what percentage of available network bandwidth isbeing used by each of the servers 402 a-402 b. This information can thenbe graphed by one or more processors, which take readings directly fromthe NICs 410 a-410 b and/or the cloud service hypervisor device 414,along with known maximum network bandwidth capabilities for each of theservers 402 a-402 b.

For example, consider graph 502 and graph 504 in FIGS. 5A-5B, whichrespectively depict network bandwidth utilization percentages of theserver #1 (server 402 a) and the server #2 (server 402 b) depicted inFIG. 4. That is, each server and/or its NIC is designed to be able toexchange a certain rate of data (typically in megabits per second) toand from a network, such as a network that interconnects the servers 402a-402 b to one another, and/or to other devices such as client computer404 and cloud service hypervisor device 414 in FIG. 4. As shown in graph504, only 27% of the available (i.e., designed) network bandwidth iscurrently being used by server #2. However, as shown in graph 502, 80%of the available network bandwidth is currently being used by server #1.

As shown in FIG. 6, if servers such as server #1 and/or server #2 usemore than 70% of their nominal (available/designed) network bandwidth,then delays in handling work increase dramatically (e.g.,asymptotically). That is, even if server #1 has plenty of capacity inits memory, processors, etc., there still is a degradation in theperformance of server #1 in responding to work orders if more than 70%of its nominal network bandwidth is being used.

Many issues can contribute to the degradation in response times to workorders and other requests of resources (e.g., virtual machines) ifnetwork bandwidth is exceeded for a particular server. For example, theNIC may simply be overloaded, thus creating a bottleneck in the pathwaybetween a requester (e.g., client computer 404 in FIG. 4) and a server(e.g., server #1 (402 a) in FIG. 4). In this embodiment, readings from aNIC (e.g., NIC 410 a in FIG. 4) are taken directly by the cloud servicehypervisor device 414, which then reallocates the placement of activeVMs to another server (e.g., server #2). Thus, all functions areperformed using hardware components of the server cloud 400, therebyimproving the performance of the server cloud 400 without any humanintervention.

Another factor that can affect the response time if the networkbandwidth is overtaxed is overworked input/output buffers. In one ormore embodiments of the present invention, network traffic sent to NIC410 a is initially stored in a buffer 416. If buffer 416 is full, thenthe data/traffic/messages are either returned to the client computer 404with an error message, or they are stored in a slower non-volatilememory (NVM) 418 within the NIC 410 a. Either scenario results in adegradation in response times to the messages/requests from the clientcomputer 404. In this embodiment, error messages are sent directly fromNIC 410 a to the cloud service hypervisor device 414, which thenreallocates the placement of active VMs to another server (e.g., server#2). Thus, all functions are performed using hardware components of theserver cloud 400, thereby improving the performance of the server cloud400 without any human intervention.

Regardless of what causes the degradation in response times, historicaldata may indicate that degradations occur at the trigger point (e.g.,usage of 70% of the designed network bandwidth for the server) for aparticular server, as depicted in FIG. 6. In order to alleviate thiscondition, the network bandwidth demands are reduced by removing one ormore VMs from the slowly-responding server (e.g., server #1). Forexample, consider now the VM movement depicted in FIG. 7.

FIG. 7 depicts tables showing a movement of various virtual machinesfrom a first physical server to a second physical server within a servercloud, based on network bandwidth percentage utilization by the firstphysical server. As shown in table 702, server #1 initially had only 20%unallocated network bandwidth (as also shown in graph 502 in FIG. 5A).Thus, server #1 was using 80% of its network bandwidth. As discussed inFIG. 6, assume that any network bandwidth usage over 70% leads to asevere increase in response delay times. Thus, the cloud servicehypervisor device 414 will remove lower priority VMs from server #1, asdepicted in table 704. Initially server #2 has 73% unallocated (i.e.,27% used) network bandwidth. Assuming that server #2's performance isthat shown in graph 600 in FIG. 6, then server #2 can handle much moreVM load without risking a reduction in response times. As depicted intable 708, the VMs that were removed from server #1 (VM3 a, VM4, VM6,and VM7) are now moved to server #2, while still leaving server #2 with43% unallocated network bandwidth (i.e., only 57% of the nominal networkbandwidth of server #2 is being utilized).

With reference now to FIG. 8, a high-level flowchart of one or moresteps performed by one or more processors and/or other hardware tooptimize performance of virtual machines in a server cloud is presented.After initiator block 802, one or more processors establish a firstmaximum network bandwidth percentage for a first physical server in theserver cloud (block 804). The maximum network bandwidth percentage is apercentage of a total network bandwidth capability designed for thefirst physical server. In one or more embodiments, this percentage isdetermined from readings from a NIC/MIB on the first physical server.The NIC provides a value that describes how much network bandwidth isbeing used, and the MIB describes the maximum network bandwidth that thefirst physical server can provide.

As depicted in graph 600 in FIG. 6, response times for operationalrequests to one or more virtual machines on the first physical serverchange beyond a predefined differential in response to the first maximumnetwork bandwidth percentage being reached. For example, upon reaching70%-80% of the designed network traffic capacity for a server, thedifferential (i.e., rate of change in the response delay times comparedwith changes in network bandwidth capacity percentages) changesradically (e.g., asymptotically—taking on the mathematicalcharacteristics of a curved line that approaches, but never reaches anasymptote line).

Note that in one or more embodiments of the present invention, thedecision to move VMs from one server to another server is not predicatedon a system being “overloaded”, but rather on the differential change inresponse times to requests. Thus, a system may be working well below itsrated nominal capacity (as is the case in graph 600 in FIG. 6), butthere is nonetheless a dramatic shift in the response delay metrics,thus prompting the movement of VMs from the first server to the secondserver.

Continuing with FIG. 8, a query is made (query block 806) as to whethera network interface card (NIC) controller device on the first physicalserver has determined that the first maximum network bandwidthpercentage for the first physical server is exceeded. The NIC controllerdevice (e.g., NIC 410 a in FIG. 4) is able to identify how much networkbandwidth (e.g., bits per second of data) is being used by the firstphysical server (e.g., physical server #1—402 a in FIG. 4). Usinginformation from the NIC 412 a regarding the maximum network bandwidththat the first server is rated for (e.g., the maximum rate at which theNIC 410 a can send/receive data), the NIC 410 a (or alternativelyanother logic, such as the cloud service hypervisor device 414) is ableto determine what percentage of the maximum rated network bandwidth isbeing used by the first physical server.

As described in block 808 of FIG. 8, in response to the NIC controllerdevice on the first physical server determining that the first maximumnetwork bandwidth percentage for the first physical server is exceeded,a cloud service hypervisor device (e.g., the cloud service hypervisordevice 414 in FIG. 4) moves one or more virtual machines on the firstphysical server to a second physical server (e.g., physical server#2—402 b in FIG. 4) in the server cloud (e.g., server cloud 400 in FIG.4).

In an embodiment of the present invention, the first physical serversupports a first set of virtual machines and a second set of virtualmachines. In the example presented in FIG. 7, server #1 supports twosets of virtual machines (VMs). The first set of VMs has beenprioritized over the second set of VMs. That is, VM1, VM2, and VM5 fromserver #1 make up a first set of VMs having VMs that have been(respectively) prioritized as having 1, 3, 1 priority ratings. A secondset of VMs from server #1 is made up of VM3 a, VM4, VM6, and VM7, all ofwhich have lower priority ratings of 5. Thus, in order to reallocate VMsbetween the server #1 and the server #2 in a manner that causes theleast amount if disruption, the VMs from the second set of VMs (VM3 a,VM4, VM6, and VM7) are migrated to server #2, while VMs from the firstset of VMs (VM1, VM2, and VM5) remain in server #1. Moving the VMs(e.g., by the server cloud hypervisor device 414 shown in FIG. 4) causesa network bandwidth percentage for the first physical server to dropbelow the first maximum network bandwidth percentage.

Various processes can be used by one or more processors to automaticallyprioritize the VMs, and thus to determine which VMs should be migratedto another server (e.g., server #2—402 b in FIG. 4) and which VMs shouldremain on the first server (e.g., server #1—402 a in FIG. 4).

In one embodiment, one or more processors prioritize the first set ofvirtual machines over the second set of virtual machines according to alength of time that applications have been continuously executing on thevirtual machines. For example, assume in FIG. 7 that VM1, VM2, and VMShave been running for 12 hours straight, while VM3 a, VM4, VM6, and VM7have only been running for the past 1-2 hours. To disrupt VM1, VM2, andVMS (e.g., by moving them server #2) may cause all of their work to becompromised and/or lost, since the work would have to be paused, statesmoved, etc. Having this information (length of operation) allows adevice (e.g., the cloud service hypervisor device 414) to intelligentlydecide which VMs should be migrated.

In one embodiment, one or more processors prioritize the first set ofvirtual machines over the second set of virtual machines according to adependency on the virtual machines by other virtual machines. Forexample, assume in FIG. 7 that VM1, VM2, and VMS are being used by otherVMs (not shown) and/or other servers. To move them to another serverwould require that all interaction between VM1, VM2, and VMS and theother VMs be suspended while VM1, VM2, and VMS are migrated to server#2. This movement would also require that a notification be sent to theother VMs, informing the other VMs of the address/location of VM1, VM2,and VMS, an update on any new protocols that the move required, etc.Having this information (number of dependent VMs/servers) allows adevice (e.g., the cloud service hypervisor device 414) to intelligentlydecide which VMs should be migrated.

In one embodiment of the present invention, one or more processorspredict future demands on the first physical server based on a quantityof virtual machines in the first set of virtual machines that have beenprioritized over the second set of virtual machines. For example, assumethat cloud service hypervisor device 414 recognizes that there are 7 VMsrunning on server #1 (see FIG. 7). Cloud service hypervisor device 414also recognizes that there are only 3 VMs running on server #2. Cloudservice hypervisor device 414 takes this information to predict thatserver #1 will be selected over server #2 for supporting future VMs.That is, server #1 may be cheaper to lease space from than server #2,server #1 may have a better track record for reliability than server #2,server #1 may have better security hardware/software systems installedthereon than server #2, etc. Whatever the reason, server #1 is known tosupport more VMs historically, and thus a prediction is made that thetrend (of server #1 being busier than server #2) will continue. Thisallows the cloud service hypervisor device 414 to take proactive steps,such as configuring more physical servers that match the capabilities(network bandwidth, instructions execution rate (i.e., “throughput”),power usage, etc.) and components (CPU, memory, NIC, etc.) of server #1for future usage.

In one embodiment of the present invention, one or more processorspredict that the maximum network bandwidth percentage is reached inresponse to the response time changing asymptotically. For example, asshown in FIG. 6, the response delay time increase in an asymptoticmanner (i.e., the curve of the line shown in FIG. 6 is asymptotic curve,such that the distance between the curve for R(X) and the line(asymptote) at the right of the graph 600 approaches zero as the curvefor R(X) and the line at the right of the graph 600 tend to infinity).This asymptotic curve provides mathematical evidence of the significantchange that occurs after the network bandwidth capacity percentage for aserver exceeds 70% or some other predefined (from historical data and/orcomponent analytics) level.

In one embodiment of the present invention, one or more processors sumnetwork bandwidth requirements for all virtual machines executing in thefirst physical server, and then determine that the first maximum networkbandwidth percentage for the first physical server is exceeded based onsummed network bandwidth requirements for all virtual machines executingin the first physical server. For example, as shown in FIGS. 5A-5Band/or FIG. 7, the network bandwidth demands of the different VMs onserver #1 are summed up, thus providing the total amount of networkbandwidth being consumed by the VMs running on server #1. This totaldemand is then used to determine whether or not the network bandwidthpercentage trigger point (discussed herein) has been reached.

As described herein, a system (e.g., that shown in FIG. 4) includes aserver cloud (e.g., server cloud 400). The server cloud includesmultiple physical servers (e.g., physical servers 402 a-402 b). Thesystem also includes a network interface card (NIC) controller device(e.g., NIC 410 a in FIG. 4) on a first physical server (e.g., server#1—402 a in FIG. 4) in the server cloud. As described herein, the NICcontroller device establishes a first maximum network bandwidthpercentage for the first physical server in the server cloud, where themaximum network bandwidth percentage is a percentage of a total networkbandwidth capability designed for the first physical server, and whereresponse time for operational requests to one or more virtual machineson the first physical server changes beyond a predefined differential inresponse to the first maximum network bandwidth percentage beingreached. The NIC controller also determines that the first maximumnetwork bandwidth percentage for the first physical server is exceeded.A cloud service hypervisor device (e.g., cloud service hypervisor device414), in response to the NIC controller device on the first physicalserver determining that the first maximum network bandwidth percentagefor the first physical server is exceeded, moves one or more virtualmachines on the first physical server to a second physical server in theserver cloud.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the presentinvention. As used herein, the singular forms “a”, “an” and “the” areintended to include the plural forms as well, unless the context clearlyindicates otherwise. It will be further understood that the terms“comprises” and/or “comprising,” when used in this specification,specify the presence of stated features, integers, steps, operations,elements, and/or components, but do not preclude the presence oraddition of one or more other features, integers, steps, operations,elements, components, and/or groups thereof.

The corresponding structures, materials, acts, and equivalents of allmeans or step plus function elements in the claims below are intended toinclude any structure, material, or act for performing the function incombination with other claimed elements as specifically claimed. Thedescription of various embodiments of the present invention has beenpresented for purposes of illustration and description, but is notintended to be exhaustive or limited to the present invention in theform disclosed. Many modifications and variations will be apparent tothose of ordinary skill in the art without departing from the scope andspirit of the present invention. The embodiment was chosen and describedin order to best explain the principles of the present invention and thepractical application, and to enable others of ordinary skill in the artto understand the present invention for various embodiments with variousmodifications as are suited to the particular use contemplated.

Any methods described in the present disclosure may be implementedthrough the use of a VHDL (VHSIC Hardware Description Language) programand a VHDL chip. VHDL is an exemplary design-entry language for FieldProgrammable Gate Arrays (FPGAs), Application Specific IntegratedCircuits (ASICs), and other similar electronic devices. Thus, anysoftware-implemented method described herein may be emulated by ahardware-based VHDL program, which is then applied to a VHDL chip, suchas a FPGA.

Having thus described embodiments of the present invention of thepresent application in detail and by reference to illustrativeembodiments thereof, it will be apparent that modifications andvariations are possible without departing from the scope of the presentinvention defined in the appended claims.

What is claimed is:
 1. A processor-implemented method of managingvirtual machines that execute on physical servers in a server cloud, themethod comprising: establishing, by one or more processors, a firstmaximum network bandwidth percentage for a first physical server in theserver cloud, wherein the first maximum network bandwidth percentage isa percentage of a total network bandwidth capability designed for thefirst physical server, wherein a response time for operational requeststo one or more virtual machines on the first physical server changesbeyond a predefined differential in response to the first maximumnetwork bandwidth percentage being reached, and wherein the predefineddifferential is a rate of change in response delay times for the firstphysical server compared with changes in network bandwidth capacitypercentages for the first physical server; determining, by the one ormore processors, that the predefined differential has been exceeded;determining, by a network interface card (NIC) controller device on thefirst physical server, that the first maximum network bandwidthpercentage for the first physical server is exceeded; in response to theNIC controller device on the first physical server determining that thefirst maximum network bandwidth percentage for the first physical serveris exceeded and that the predefined differential is exceeded, moving, bya cloud service hypervisor device, one or more virtual machines on thefirst physical server to a second physical server in the server cloud;wherein the first physical server supports a first set of virtualmachines and a second set of virtual machines and prioritizes, by theone or more processors, the first set of virtual machines over thesecond set of virtual machines; moving, by the server cloud hypervisordevice, the virtual machines from the second set of virtual machines tothe second physical server until a network bandwidth percentage for thefirst physical server drops below the first maximum network bandwidthpercentage, wherein virtual machines from the first set of virtualmachines remain on the first physical server; predicting, by the one ormore processors, future demands on the first physical server, beinghigher than a demand on the second physical server, based on a quantityof virtual machines in the first set of virtual machines; andconfiguring, by the cloud service hypervisor device, multiple physicalservers that match network bandwidth, throughput, power usage, andhardware components of the first physical server, wherein the multiplephysical servers are configured to support future virtual machines thatmeet the future demands on the first physical server, and wherein eachof the multiple physical servers minors a configuration of the firstphysical server.
 2. The processor-implemented method of claim 1, furthercomprising: prioritizing, by the one or more processors, the first setof virtual machines over the second set of virtual machines according toa length of time that applications have been continuously executing onthe virtual machines.
 3. The processor-implemented method of claim 1,further comprising: prioritizing, by the one or more processors, thefirst set of virtual machines over the second set of virtual machinesaccording to a dependency on the virtual machines by other virtualmachines.
 4. The processor-implemented method of claim 1, furthercomprising: determining, by the one or more processors, that the maximumnetwork bandwidth percentage is reached in response to the response timechanging asymptotically relative to changes in network bandwidthchanges, wherein asymptotic response time changes have mathematicalcharacteristics of a curved line that approaches, but never reaches anasymptote line, wherein response delay times increase in an asymptoticmanner such that a distance between an asymptotic curve representing anincrease in the asymptotic response time changes approaches but neverreaches a line representing the total network bandwidth capabilitydesigned for the first physical server.
 5. The processor-implementedmethod of claim 1, further comprising: summing, by the one or moreprocessors, network bandwidth requirements for all virtual machinesexecuting in the first physical server; and determining, by the one ormore processors, that the first maximum network bandwidth percentage forthe first physical server is exceeded based on summed network bandwidthrequirements for all virtual machines executing in the first physicalserver.
 6. The processor-implemented method of claim 1, furthercomprising: determining, by the cloud service hypervisor device, thatinput/output buffers on the first physical server are full, wherein theinput/output buffers initially store network traffic to the firstphysical server; and determining, by the cloud service hypervisordevice, that the first maximum network bandwidth percentage for thefirst physical server is exceeded based on the input/output buffersbeing full.